code: def test_pad_error():
      batch_size = 2
      input_max_shape = (5, 5, 3)
      device = "cpu"
      axes = None
      layout = "HWC"
      axis_names = "H"
      align = 0
      shape_arg = None
  
      eii = RandomlyShapedDataIterator(
          batch_size, max_shape=input_max_shape
      )
      pipe = PadSynthDataPipeline(
          device,
          batch_size,
          iter(eii),
          axes=axes,
          axis_names=axis_names,
          align=align,
          shape_arg=shape_arg,
          layout=layout,
      )
  
      pipe.build()
      with assert_raises(
          RuntimeError,
          glob="Values of `align` argument must be positive.",
      ):
          pipe.run()
  
imports: import numpy
  import nvidia.dali
  import nvidia.dali.fn
  import nvidia.dali.math
  import nvidia.dali.ops
  import nvidia.dali.types
  from nvidia.dali import Pipeline, pipeline_def
  from nvidia.dali.backend_impl import TensorListGPU
  from nose_utils import assert_raises
  from test_utils import RandomlyShapedDataIterator, generator_random_axes_for_3d_input, generator_random_data, as_array
label_desc: Use image node_id 3 for calling a global function with example usage: test_pad_error() without return types